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Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method

机译:差分3D面部识别:将3D添加到最先进的2D方法

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Active illumination is a prominent complement to enhance 2D face recognition and make it more robust, e.g., to spoofing attacks and low-light conditions. In the present work we show that it is possible to adopt active illumination to enhance state-of-the-art 2D face recognition approaches with 3D features, while bypassing the complicated task of 3D reconstruction. The key idea is to project over the test face a high spatial frequency pattern, which allows us to simultaneously recover real 3D information plus a standard 2D facial image. Therefore, state-of-the-art 2D face recognition solution can be transparently applied, while from the high frequency component of the input image, complementary 3D facial features are extracted. Experimental results on ND-2006 dataset show that the proposed ideas can significantly boost face recognition performance and dramatically improve the robustness to spoofing attacks.
机译:主动照明是提高2D面部识别的突出补充,使其更加强大,例如欺骗攻击和低光的条件。在本工作中,我们表明可以采用主动照明来增强具有3D特征的最先进的2D面识别方法,同时绕过3D重建的复杂任务。关键思想是将测试面部投射高空间频率模式,其允许我们同时恢复真实的3D信息加上标准的2D面部图像。因此,可以透明地应用最先进的2D面部识别解决方案,而来自输入图像的高频分量,提取互补的3D面部特征。在ND-2006数据集上的实验结果表明,提议的思想可以显着提高面部识别性能,从而大大提高欺骗攻击的鲁棒性。

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